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Found 217 Skills
Get verified emails and phones for contacts found by people-search. Takes LinkedIn profiles from the Extruct people table and enriches them via contact enrichment providers like Prospeo or Fullenrich. Supports single-provider and waterfall modes. Outputs a contact CSV ready for email-generation. Triggers on: "get emails", "find emails", "enrich contacts", "email finder", "get phone numbers", "enrich people", "contact enrichment", "verify emails", "email enrichment".
Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.
Cube.js integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cube.js data.
Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.
Parse, analyze, and process SARIF (Static Analysis Results Interchange Format) files. Use when reading security scan results, aggregating findings from multiple tools, deduplicating alerts, extracting specific vulnerabilities, or integrating SARIF data into CI/CD pipelines.
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.
Instructions for applying mathematical transformations to temperature data based on rules in weather-orchestration/input.md
Calculate the deviation of asset prices relative to the long-term exponential growth trend line, assess whether the current period falls within a historical extreme range, and optionally perform macro factor analysis to evaluate the market regime.
Analyze the BTC market using a custom momentum theory with nested multi-timeframe analysis (2-day/1-day/12h/6h/4h/2h/1h/30min). Identify uptrend segments, downtrend segments, discrete regulation, unit adjustment cycles, continuous gap divergences, and DIF-DEA divergences, and generate momentum reports with detailed attribute judgments and trading signals. Automatically activates when users inquire about BTC momentum, segment status, MACD analysis, cycle judgment, or divergence detection.
Identify key themes and concerns raised by analysts during earnings calls, including specific analyst attribution and topic categorization.